Access and presentation of files based on semantic proximity to current interests

ABSTRACT

A method for managing and rendering one or more information nodes relative to a current focus. The method receives one or more principal topics from an analysis of the information nodes. The method determines a topic vector from a similarity of a first information node to each of the principal topics and a map from the topic vector to a storage location of the first information node. The method determines one or more current topics from a second information node that has been recently accessed by a user and a current focus vector from a similarity of the one or more current topics to the one or more principal topics. The method renders the current focus vector and the first information node according to a rendering algorithm that is applied to the current focus vector and the first information node.

BACKGROUND OF THE INVENTION

The present invention relates generally to the field of informationorganization, access, and presentation and more particularly to themanagement and presentation of information based on the relevance of itssemantic content to a user's current interests.

The management and presentation of large amounts of information to auser in a manner that does not impose a high cognitive burden is agrowing challenge as the amount of data that is available to beconsidered and analyzed steadily increases. Machines can help byperforming a triage on available information, estimating what isrelevant to a current focus and thereby decreasing the amount ofinformation a user must consider. The amount of relevant informationconsidered is one component of the burden, but equally significant isthe form in which the information is presented. If information can bepresented in a way that simply reflects relationships among theinformation considered and the strength of these relationships, then thecognitive burden imposed on the user can sometimes be decreased.

A force directed graph is a means for presenting information and therelationships between information. The idea of a force directed graph isto spatially represent a set of nodes, where a node is a data orinformation (e.g., text, a word, an email), such that nodes rendered inproximity to one another tend to be more intimately connected to oneanother along some dimension or set of dimensions (e.g., a topicdiscussed in the nodes if, say, the node represent text), and such thatthe attraction among like nodes and repulsion among non-like nodes obeysa force-distance relationship known from physics. Force-directed graphdrawing algorithms are a class of algorithms for drawing graphs in anaesthetically pleasing manner.

SUMMARY

A method for managing and rendering one or more information nodesrelative to a current focus. The method receives one or more principaltopics from an analysis of a content of the one or more informationnodes. The method further determines a topic vector from a similarity ofa content of a first information node in the one or more informationnodes to each of the one or more principal topics. The method furtherdetermines a map from the topic vector to a storage location of thefirst information node. The method further determines one or morecurrent topics from a content of a second information node that has beenrecently accessed by a user. The method further determines a currentfocus vector from a similarity of the one or more current topics to eachof the one or more principal topics. The method further renders arepresentation of the current focus vector and a representation of thefirst information node according to a rendering algorithm that isapplied to the current focus vector and the first information node,wherein a position and a size of the representation of the current focusvector and of the first information node is determined by the renderingalgorithm.

Another embodiment of the present invention provides a computer programproduct for managing and rendering one or more information nodesrelative to a current focus, based on the method described above.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 depicts a block diagram of a computer system attached to anetwork and user interfaces in accordance with an embodiment of thepresent invention;

FIG. 2 depicts a block diagram of a semantic proximity system that isdepicted in FIG. 1, in accordance with an embodiment of the presentinvention;

FIG. 3 depicts an example force directed graph in accordance with anembodiment of the present invention;

FIG. 4 depicts a flow chart for an operation of the semantic proximitysystem depicted in FIG. 2, in accordance with an embodiment of thepresent invention; and

FIG. 5 depicts a block diagram of the computer system that is depictedin FIG. 1, in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

Detailed embodiments of the present invention are disclosed herein withreference to the accompanying drawings. It is to be understood that thedisclosed embodiments are merely illustrative of potential embodimentsof the present invention and may take various forms. In addition, eachof the examples given in connection with the various embodiments isintended to be illustrative, and not restrictive. Further, the figuresare not necessarily to scale, some features may be exaggerated to showdetails of particular components. Therefore, specific structural andfunctional details disclosed herein are not to be interpreted aslimiting, but merely as a representative basis for teaching one skilledin the art to variously employ the present invention.

References in the specification to “one embodiment”, “an embodiment”,“an example embodiment”, etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to affect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

In an embodiment of the present invention, the content of a file iscompared to a set of principal topics when it is stored in the filesystem and that comparison is recorded in a file system index. The indexis a data structure that maps a similarity of the file's content to eachof the principal topics to the storage location of the file. The file isaccessed by presenting the topics in the file's content to the index. Inan embodiment, a user's recent accesses are monitored and their contentis compared to the set of principal topics. The result of thiscomparison is used to create a current focus for the user.Representations of the current focus and some or all of the files in thefile system are rendered visually in a way that expresses the semanticsimilarity between the content of the files and the current focus. Forexample, files with similar content are rendered closer to one another(with the distance depending on how similar their contents are) whilefiles with dissimilar content are rendered farther apart. The user canaccess a file (e.g., one that is closely related to the user's currentfocus) by selecting its rendered representation. In an embodiment, aforce directed graph is used to render the representations of the filesand the current focus.

Embodiments of the present invention recognize that the cognitive burdenof a user is sometimes decreased by presenting files and a user'scurrent interests (a current focus) in a way that reflects the strengthof their semantic similarity while providing a method for the user toaccess them, without the user having to access and navigate atraditional hierarchical file system.

FIG. 1 depicts computer system 101 that, in some scenarios andembodiments, includes I/O interface 104, processor 105, storage 107, andmemory 106. In an embodiment, semantic proximity system 108 resides inmemory 106. User interfaces 102 and network 103 are connected tocomputer system 101. Semantic proximity system 108 generates a currentinterest file from recent user activity and presents representations ofit and other files to reflect the similarity and/or dissimilarity ofcontent among the files to the user. A file can be any file whoseinformation content can be interpreted and given meaning. For example, afile may include, in whole or part, a document (e.g., text, sourcecode), an email, audio, an image, a hologram, video, a core dump, orother interpretable information.

FIG. 2 depicts the functions in semantic proximity system 108 in moredetail. In some scenarios and embodiments, semantic proximity system 108includes user control 201, context manager 202, principal topicsgenerator 203, current focus manager 204, node topic vector generator206, current focus vector generator 207, storage manager 208, andrendering manager 210. In some scenarios and embodiments, current focusmanager 204 includes current topics generator 205, storage manager 208includes index manager 209, and rendering manager 210 includes algorithmmanager 211.

In an embodiment, user control 201 is an interface for control inputfrom a user that enables the user to modify a functionality andconfiguration of semantic proximity system 108. Context manager 202manages a selection of information nodes (stored in storage 107) thatare rendered (by rendering manager 210) together with a current focus ofa user (generated by current focus manager 204).

In an embodiment, context manager 202 selects all or some of the files(also called information nodes) in storage 107 to be rendered with acurrent focus. In an embodiment, the selection of the information nodesis based on input from user control 201. In an embodiment, a userselects the information nodes to be rendered with a current focus. In anembodiment, a user guides a selection of information nodes by providinga characterization of the information nodes to be selected for renderingwith a current focus to context manager 202 and the characterization isused by context manager 202 to select information nodes in storage 107that meet the characterization. In an embodiment, the information nodesto be rendered are selected by an algorithm.

In an embodiment, principal topics generator 203 performs an analysis ofthe content of the information nodes in the selection of informationnodes selected by context manager 202 and extracts one or more topicsfrom each information node. It then generates a set of principal topicsby selecting the most pervasive and representative topics from thetopics that principal topics generator generated from each informationnode. An information node may include, in whole or part, a document(e.g., text, source code), an email, audio (e.g., speech), an image, ahologram, video, a core dump, or other interpretable information. Theanalysis identifies and generates a set of principal topics, i.e., theprimary topics that are in the content of the information nodes in theselection of information nodes. In an embodiment, if the informationnodes in the selection of information nodes contain text information,principal topics generator 203 uses a Latent Dirichlet Allocation (LDA)algorithm to perform the analysis. In another embodiment, if theinformation nodes in the selection of information nodes contain textinformation, principal topics manager 203 uses a probabilistic latentsemantic indexing (pLSI) algorithm to perform the analysis. In otherembodiments, principal topics generator 203 uses other algorithms toperform the analysis that are appropriate to the type of informationcontained in the information nodes in the selection of informationnodes. For example, if an information node contains video, an algorithmthat can analyze the video and characterize its content (e.g., a carchase, a wedding, or a rocket launch) is used by principal topicsgenerator 203 to perform the analysis.

In an embodiment, node topic vector generator 206 receives the selectionof information nodes from context manager 202 and the set of principaltopics (that were generated from the content of the selection ofinformation nodes) from principal topics generator 203. Node topicvector generator 206 generates a set of node topic vectors, one nodetopic vector for each information node in the selection of informationnodes. In an embodiment, a node topic vector contains a list of valuesthat reflect the affinity that the information node has for eachprincipal topic. Values in a node topic vector are in one-to-onecorrespondence with the principal topics in the set of principal topics.

In an embodiment, current focus manager 204 monitors and records theinformation accessed during a user's recent information access activity.For example, current focus manager 204 monitors and records a user'saccess to web sites, files (including emails), and multimedia (e.g.,images, audio, video, movies, and holograms) as well as the user'spotential editing of the files and media.

In an embodiment, current topics generator 205 analyzes the informationin the record of the user's recent information access activity andidentifies a set of primary topics (i.e., prevalent topics). In anembodiment, current topics generator 205 generates an artificialdocument from set of current topics with a content that reflects theprevalence of each primary topic in the user's recent information accessactivity. In an embodiment, the artificial document represents theuser's current focus.

In an embodiment, if the record includes text information, then currenttopics generator 205 uses a Latent Dirichlet Allocation (LDA) algorithmto analyze the text information for topics. In another embodiment, ifthe record includes text information, then current topics generator 205uses a probabilistic latent semantic indexing (pLSI) algorithm toanalyze the text information for topics. In other embodiments, currenttopics generator 205 uses other algorithms to perform the analysis thatare appropriate to the type of information contained in the recentinformation. In an embodiment, current focus manager 204 forms anartificial document with a content that reflects the current topics inthe set of current topics in proportion to their strength in the user'srecent information access activity.

In an embodiment, current focus vector generator 207, receives theartificial document from current focus manager 204 and the set ofprincipal topics (that were generated from the content of the selectionof information nodes) from principal topics generator 203. Current focusvector generator 207 generates one current focus vector that reflectsthe affinity that the artificial document (which reflects the user'scurrent focus) has for each of the principal topics in the set ofprincipal topics. Values in the current focus vector are in one-to-onecorrespondence with the principal topics in the set of principal topics.

In an embodiment, rendering manager 210 receives the current focusvector from current focus vector generator 207 and the set of node topicvectors from node topic vector generator 206 and visually rendersrepresentations of them in a way that reveals an affinity (i.e.,similarity) that a node topic vector has for the user's current focus.In an embodiment, the affinity that a given information node (thecontent of which is measured by a node topic vector) has for the user'scurrent focus (the content of which is measured by the current focusvector) is calculated by taking the inner product of the two vectors.The inner product (also called dot product or scalar product) of twovectors is an algebraic operation that returns a single value. The valueis the magnitude of one vector in the direction of the other vector inthe vector space in which the vectors are defined. A node vector and thecurrent focus vector are in a topic vector space that has the principaltopics as its basis vectors, and has a dimension equal to the number ofprincipal topics. In the topic vector space the inner product of twovectors is a measure of the similarity of the two vectors, i.e., ameasure of the similarity of a content of an information node(represented by a node topic vector) to the content of a user's currentfocus (represented by the current focus vector).

In some scenarios and embodiments, algorithm manager 212, a function inrendering manager 210, renders a representation of each of theinformation nodes (that node topic vector generator 206 receives fromcontext manager 202) and the current focus (represented by the currentfocus vector) in positions based on the strength of similarities oftheir contents with each other and with the current focus. In anembodiment, algorithm manager generates a force directed graph of therepresentations of the information nodes and the current focus. In anembodiment, a representation of the current focus is centrally locatedin a rendering with an edge (a line) from the current focusrepresentation to each information node representation. In anembodiment, each of the principal topics is also rendered as a specialinformation node, a “topic” node, with one or more edges between a topicnode and the information nodes. In an embodiment, an attractive force onedge between an information node and a topic node is in proportion tothe affinity of the information node with a topic represented by thetopic node. In an embodiment, physical forces of attraction andrepulsion between rendered representations of information nodes, thecurrent focus, and, in an embodiment, the principal topics, are used tocreate a resulting natural arrangement of the representations. That is,algorithm manager 211 renders the representations in the positions thatare in equilibrium with the forces acting on the representations. In anembodiment, spring-like attractive forces based on Hooke's law(attractive force is proportional to distance) are used to attract pairsof representations towards each other, while simultaneously repulsiveforces like those of electrically charged particles based on Coulomb'slaw (where the repulsive force of like charges is inversely proportionalto the square of the distance, i.e., half the distance quadruples theforce) are used to separate all pairs of representations. In anembodiment, the strength of the attractive force between arepresentation of the current focus and a representation of aninformation node is in direct proportion to the value of the innerproduct of the current focus vector and the node topic vector that isassociated with the information node.

In an embodiment, a user can access an information node whoserepresentation is displayed in a rendering by selecting therepresentation of the information node in the rendering. In anembodiment, when an information node (i.e., a file) is stored in storage107, a topic vector is generated for the information node and isassociated with the location of the information node in storage 107. Thelocation is mapped to the topic vector of the information node by indexmanager 209 in storage manager 208 in an index. The index provides alocation of an information node in storage 107 when the index isaccessed by the topic vector of the information node. In effect, theindex enables an information node to be accessed by its contents, whichare represented by its topic vector. Such an index is often termed aninverted index.

In an embodiment, rendering manager 210 renders an information node thatcontains words of text as a wordle (i.e., a word cloud). The wordle is agroup of commonly occurring words in the information node. In anembodiment, the size of each word in a wordle is a function of itsprevalence in the information node. In an embodiment, the size a word ina wordle of an information node is in direct proportion to theprevalence of the word in the information node. In another embodiment,the size of prevalent words are exaggerated and the size of infrequentwords are minimized. In an embodiment, rendering manager 210 accessesstorage 107 for an information node using its associated node topicvector that rendering manager 210 receives from node topic vectorgenerator 206. Storage manager 208 submits the node topic vector toindex manager, which accesses the inverted index with the node topicvector and acquires the location of the information node in storage 107.Algorithm manager 211 coverts the contents of the information node intoa wordle and renders the wordle. In an embodiment, algorithm manager 211renders a position of the center of a wordle as an equilibrium position(for the information node from which the wordle is derived) in a forcedirected graph.

In an embodiment, rendering manager 210 in semantic proximity system 108renders the similarity of the contents of the collective informationnodes of a group of users relative to the current focus of each user ina rendering for each user.

FIG. 3 depicts example force directed graph with representations (i.e.,nodes) 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, and 312.In an embodiment, node 301 represents the current focus node, nodes 305,306, 307, 308, 309, 310, and 311 represent the selected informationnodes, and, in an embodiment, nodes 302, 303, and 304 representprincipal topic nodes. The proximity of an information node (e.g., node308) to the current focus node (node 301), reflects the similarity ofcontent the nodes share, i.e., an affinity of the content of one node tothe content of the other node. In an embodiment, edges are renderedbetween information nodes and the principal topic nodes, as well asbetween the focus node and the principal topic nodes. Nodes which arenot connected by an edge are repelled from one another.

Force directed graphs can be generated in many ways and can use avariety of attractive and repulsive functions to arrange the nodesrendered in them. In an embodiment, the focus node can attract theinformation nodes and the topic nodes can attract the information nodes.In an embodiment, the focus node can attract the information nodes andthere is no attraction between the topic nodes and the informationnodes. In an embodiment, the edges are not rendered and are manifestonly in force and rendering calculations, and not in a rendering itself.

FIG. 4 depicts the operational steps performed by semantic proximitysystem 108, in an embodiment and scenario. Information nodes (files) arereceived and stored in storage 107 in step 402. One or more informationnodes in storage 107 are selected for rendering by context manager 202in step 404. A set of principal topics is generated from the selectedinformation nodes by principal topics generator 203 in step 406. A nodetopic vector is generated for each of the selected information nodes bynode topic vector generator 206 in step 408. A user's recent accessesare monitored and recorded by current focus manager 204 in step 410. Thecontent of the user's recent accesses are analyzed and a set of primarytopics are identified in the recent accesses by current topics generator205 in step 412. A current focus vector is generated from the primarytopics by current focus vector generator 207 in step 414.Representations of the selected information nodes and the current focusare rendered by algorithm manager 211 in step 416.

FIG. 5 depicts computer system 500 that is an example a computer systemthat hosts the functions of semantic proximity system 108 in computersystem 101. Computer system 500 includes communications fabric 502,which provides communications between computer processor(s) 504, memory506, persistent storage 508, communications unit 510, and input/output(I/O) interface(s) 512. Communications fabric 502 can be implementedwith any architecture designed for passing data and/or controlinformation between processors (such as microprocessors, communicationsand network processors, etc.), system memory, peripheral devices, andany other hardware components within a system. For example,communications fabric 502 can be implemented with one or more buses.

Memory 506 and persistent storage 508 are computer readable storagemedia. In this embodiment, memory 506 includes random access memory. Inan embodiment, memory 506 is an example of memory 106 and persistentstorage 508 is an example of storage 107. In general, memory 506 caninclude any suitable volatile or non-volatile computer readable storagemedia. Cache 516 is a fast memory that enhances the performance ofprocessors 504 by holding recently accessed data and data near accesseddata from memory 506.

Program instructions and data used to practice embodiments of thepresent invention may be stored in persistent storage 508 for executionby one or more of the respective processors 504 via cache 516 and one ormore memories of memory 506. In an embodiment, persistent storage 508includes a magnetic hard disk drive. Alternatively, or in addition to amagnetic hard disk drive, persistent storage 508 can include a solidstate hard drive, a semiconductor storage device, read-only memory(ROM), erasable programmable read-only memory (EPROM), flash memory, orany other computer readable storage media that is capable of storingprogram instructions or digital information.

The media used by persistent storage 508 may also be removable. Forexample, a removable hard drive may be used for persistent storage 508.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage508.

Communications unit 510, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 510 includes one or more network interface cards.Communications unit 510 may provide communications through the use ofeither or both physical and wireless communications links. Programinstructions and data used to practice embodiments of the presentinvention may be downloaded to persistent storage 508 throughcommunications unit 510.

I/O interface(s) 512 allows for input and output of data with otherdevices that may be connected to each computer system. For example, I/Ointerface 503 may provide a connection to external devices 518 such as akeyboard, keypad, a touch screen, and/or some other suitable inputdevice. External devices 518 can also include portable computer readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data used to practiceembodiments of the present invention can be stored on such portablecomputer readable storage media and can be loaded onto persistentstorage 508 via I/O interface(s) 512. I/O interface(s) 512 also connectto a display 520.

Display 520 provides a mechanism to display data to a user and may be,for example, a computer monitor.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The terminology used herein was chosen to best explain the principles ofthe embodiment, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the presentinvention. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise.

Each respective figure, in addition to illustrating methods of andfunctionality of the present invention at various stages, alsoillustrates the logic of the method as implemented, in whole or in part,by one or more devices and structures. Such devices and structures areconfigured to (i.e., include one or more components, such as resistors,capacitors, transistors and the like that are connected to enable theperforming of a process) implement the method of merging one or morenon-transactional stores and one or more thread-specific transactionalstores into one or more cache line templates in a store buffer in astore cache. In other words, one or more computer hardware devices canbe created that are configured to implement the method and processesdescribed herein with reference to the Figures and their correspondingdescriptions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiment, the practical application or technicalimprovement over technologies found in the marketplace, or to enableother of ordinary skill in the art to understand the embodimentsdisclosed herein.

Embodiments of the present invention may be used in a variety ofelectronic applications, including but not limited to advanced sensors,memory/data storage, semiconductors, microprocessors and otherapplications.

A resulting device and structure, such as an integrated circuit (IC)chip can be distributed by the fabricator in raw wafer form (that is, asa single wafer that has multiple unpackaged chips), as a bare die, or ina packaged form. In the latter case the chip is mounted in a single chippackage (such as a plastic carrier, with leads that are affixed to amotherboard or other higher level carrier) or in a multichip package(such as a ceramic carrier that has either or both surfaceinterconnections or buried interconnections). In any case the chip isthen integrated with other chips, discrete circuit elements, and/orother signal processing devices as part of either (a) an intermediateproduct, such as a motherboard, or (b) an end product. The end productcan be any product that includes integrated circuit chips, ranging fromtoys and other low-end applications to advanced computer products havinga display, a keyboard or other input device, and a central processor.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

While the invention has been described in detail in connection with onlya limited number of embodiments, it should be readily understood thatthe invention is not limited to such disclosed embodiments. Rather, theinvention can be modified to incorporate any number of variations,alterations, substitutions or equivalent arrangements not heretoforedescribed, but which are commensurate with the spirit and scope of theinvention. Additionally, while various embodiments of the invention havebeen described, it is to be understood that aspects of the invention maybe included by only some of the described embodiments. Accordingly, theinvention is not to be seen as limited by the foregoing description. Areference to an element in the singular is not intended to mean “one andonly one” unless specifically stated, but rather “one or more.” Allstructural and functional equivalents to the elements of the variousembodiments described throughout this disclosure that are known or latercome to be known to those of ordinary skill in the art are expresslyincorporated herein by reference and intended to be encompassed by theinvention. It is therefore to be understood that changes may be made inthe particular embodiments disclosed which are within the scope of thepresent invention as outlined by the appended claims.

What is claimed is:
 1. A method for managing and rendering one or moreinformation nodes relative to a current focus, the method comprising:receiving, by a processor, one or more principal topics from a contentof one or more information nodes, wherein the one or more informationnodes includes at least one first information node; determining, by aprocessor, a topic vector from a similarity of a content of the firstinformation node to the one or more principal topics; creating, by aprocessor, a map from the topic vector to a storage location of thefirst information node; determining, by a processor, one or more currenttopics from a content of a second information node, wherein the secondinformation node is an information node that has been accessed recently;determining, by a processor, a current focus vector from a similarity ofthe one or more current topics to each of the one or more principaltopics; and rendering, by a processor, a representation of the currentfocus vector and a representation of the first information nodeaccording to a rendering algorithm, wherein the rendering algorithmdetermines a position and a size of the representation of the currentfocus vector and of the first information node.
 2. The method of claim1, wherein the receiving the one or more principal topics isaccomplished by receiving the one or more principal topics from theuser.
 3. The method of claim 1, further comprising accessing the firstinformation node in the storage location by selecting the representationof the first information node.
 4. The method of claim 1, wherein therendering algorithm includes a force directed drawing algorithm.
 5. Themethod of claim 3, wherein the rendering algorithm includes an algorithmthat renders a content of the first information node as a word cloud. 6.The method of claim 1, wherein the rendering algorithm uses thesimilarity of the one or more current topics to each of the one or moreprincipal topics to generate a position and a size of the representationof the current focus vector and of the first information node.
 7. Themethod of claim 1, wherein the topic vector and the current focus vectorare determined by using a Latent Dirichlet Allocation algorithm.
 8. Themethod of claim 1, wherein the one or more principal topics and the oneor more information nodes are periodically received and the topic vectoris periodically determined.
 9. The method of claim 1, wherein the one ormore leading topics are received from a user.
 10. The method of claim 1,wherein the first information node and the second information nodeinclude a plurality of emails.
 11. The method of claim 10, wherein therendering algorithm includes an evaluation of a commonality of a sourceand a destination of each email to a source and a destination of anotheremail in the plurality of emails.
 12. The method of claim 1, wherein thecurrent focus vector is a contrived document with a content that matchesa similarity of the one or more current topics to each of the one ormore leading topics.
 13. The method of claim 1, wherein the renderingfurther comprises a rendering of each of the principal topics.
 14. Acomputer program product for managing and rendering one or moreinformation nodes relative to a current focus, the computer programproduct comprising: one or more computer readable storage media andprogram instructions stored on the one or more computer readable storagemedia, the program instructions comprising: program instructions toreceive one or more principal topics from a content of one or moreinformation nodes, wherein the one or more information nodes includes atleast one first information node; program instructions to determine atopic vector from a similarity of a content of the first informationnode to the one or more principal topics; program instructions to createa map from the topic vector to a storage location of the firstinformation node; program instructions to determine one or more currenttopics from a content of a second information node, wherein the secondinformation node is an information node that has been accessed recently;program instructions to determine a current focus vector from asimilarity of the one or more current topics to each of the one or moreprincipal topics; and program instructions to render a representation ofthe current focus vector and a representation of the first informationnode according to a rendering algorithm, wherein the rendering algorithmdetermines a position and a size of the representation of the currentfocus vector and of the first information node.
 15. The computer programproduct of claim 14, further comprising program instruction to accessthe first information node in the storage location by selecting therepresentation of the first information node.
 16. The computer programproduct of claim 14, wherein the rendering algorithm includes a forcedirected drawing algorithm.
 17. The computer program product of claim14, wherein the rendering algorithm uses the similarity of the one ormore current topics to each of the one or more principal topics togenerate a position and a size of the representation of the currentfocus vector and of the first information node.
 18. The computer programproduct of claim 14, wherein the first information node and the secondinformation node include a plurality of emails.
 19. The computer programproduct of claim 14, wherein the current focus vector is a contriveddocument with a content that matches a similarity of the one or morecurrent topics to each of the one or more leading topics.
 20. Thecomputer program product of claim 14, wherein the rendering furthercomprises a rendering of each of the principal topics.